Social Problems of Tobacco Marketing in Southwestern Nigeria: A Behavioral Study

Tobacco industries has always shown much interest in marketing their line of products and have been very successful in portraying smoking as a socially acceptable behavior to billions of people throughout the world. Studies have shown in developed nations that tobacco marketing leads to the onset of smoking among adolescents; in Nigeria no such study has been done. The purpose of this research is to assess the potential influence of tobacco marketing on tobacco consumption and its effects on the society and among residents in the southwestern region of Nigeria. The survey was designed in which thirty-six items, self-administered questionnaire was administered to six hundred people in southwestern Nigeria using a cross-sectional design. The study involved 436 males (72.7%) and 164 females (27.3%). Of these, 336 came from rural areas and 264 came from urban areas respectively. Some 337 respondents (56.2%), indicated that they were influenced by tobacco marketing to smoke, while 263 (43.8%) indicated that they were not influenced. Chi square statistic was used to test the null hypotheses. The result shows a positive significant relationship that supports the notion that tobacco marketing has a positive influence on tobacco consumption in the study areas. This study also revealed that more males in the urban area are being influenced by tobacco marketing to smoke

Socio-Economic Impact of Energy-Related Policy on Hispanic New Mexico Attitudes, Values and Policy Perceptions

The Southwest Hispanic Research Institute at the University of New Mexico conducted a one-year study of the impact of energy-related policies on a survey sample of 584 Hispanic families in the New Mexico communities of Taos, Albuquerque and Las Cruces 0 Upon an extensive review of the research literature, the project team developed and tested sixteen hypotheses focusing on nine energy impact issues: Energy Use and Expenditures, Conservation Efforts, Market Basket Effects, Employment and Energy, Recreation and Leisure Activities, Transportation Effects, Attitudes Towards Energy Costs, Attitudes Towards Rate Structure and Evaluation of the Federal Energy Assistance Program. The data supported most the hypotheses derived from the literature but not all. Specific findings indicated that the Hispanic families in the sample have reduced their level of expenditures for energy expenses, have implemented a variety of conservation measures, have curtailed expenses for food purchases, leisure and recreational activities and for miscellaneous transportation; also, the data show significant dissatisfaction with high energy costs which are perceived to accrue benefits mostly to the energy suppliers; the respondents were in favor of a progressive rate structure that would lessen the price burden on families with low or fixed income. Not supported were hypotheses that predicted negative impacts of energy costs on employment-related activities. Lastly, the federal low-income energy assistance program in New Mexico received weak support. The study concludes with policy recommendations calling for an energy message program geared to regional and socio-cultural factors, a companion program to solarize homes and farm structures utilizing technologies suitable to the region, incentives to private sector minority entrepreneurs equipping them with solar venture capabilities that will serve local markets and create jobs, an energy safety net and an intensive greenhouse program that will protect the market basket resources of the poor, a government policy on transportation and energy that will insure access to essential formal and informal points in the health and welfare system, and lastly, a federal-state-local partnership of financial and technical assistance options at the community level to expand energy assistance and weatherization programs

Domestic Water Use and Values in Swaziland: A Contingent Valuation Analysis

The paper reports on the use of the contingent valuation method to study the determinants of Swazi households' willingness to pay (WTP) for an improvement in their water quantity and quality. A sample of 374 households was surveyed and a Tobit model was applied to explain household preferences for quality and quantity of domestic water supply and derive estimates of WTP for such a service. The results confirm that household income had a positive and statistically significant impact on WTP for both quality and quantity. Distance to the water source is positively associated with WTP regardless of the location (rural or urban) and of the household head's age, education, and gender. Current water consumption was also statistically significant for WTP for improved quantity, but with a negative sign, implying that the more a household consumes water, the less that household is WTP to have improved water quantity. Conversely, the same household would be WTP for improved water quality. Rural households showed a much higher WTP for improved water provision services than urban households. There is therefore scope to improve water service levels in Swaziland even at a higher water price. More precisely, the estimates of WTP obtained in this study indicate the possibility of introducing a demand-driven program to expand the coverage of rural tap water schemes.Resource /Energy Economics and Policy,

Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review

Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined with their use of large-scale data and the frequent need for near real-time de-cisions, means that Artificial Intelligence (AI) and Machine Learning (ML) — a branch of AI — have recently emerged as key technologies for enabling demand-side response. AI methods can be used to tackle various challenges, ranging from selecting the optimal set of consumers to respond, learning their attributes and pref-erences, dynamic pricing, scheduling and control of devices, learning how to incentivise participants in the DR schemes and how to reward them in a fair and economically efficient way. This work provides an overview of AI methods utilised for DR applications, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects. The papers are classified with regards to both the AI/ML algorithm(s) used and the application area in energy DR. Next, commercial initiatives are presented (including both start-ups and established companies) and large-scale innovation projects, where AI methods have been used for energy DR. The paper concludes with a discussion of advantages and potential limitations of reviewed AI techniques for different DR tasks, and outlines directions for future research in this fast-growing area

Quantification of ENERGY STAR® Qualification for New Homes: An Investigation of Market Impacts

Buildings represent 41% of the annual energy consumption in the United States, more than either manufacturing or transportation. As society becomes increasingly energy conscious, individuals seek new ways to reduce residential energy usage. As a result, third-party verified energy efficiency programs are gaining popularity in residential construction and offer many benefits to home builders and home buyers alike. ENERGY STAR® is a popular third-party verified construction program that reduces home energy consumption by a minimum of 15% compared to code-built homes. Obstacles to widespread implementation of the ENERGY STAR program include the added costs involved in building an ENERGY STAR qualified home and home builder reservations concerning financial return on investment. This study examined ENERGY STAR qualified home sales and compared their market performance to non-qualified homes within a ten-county region of central North Carolina. It was found that ENERGY STAR Homes sold faster and sold for higher prices than non-qualified homes. Additionally, they sold for a greater percentage of the listing price and earned a higher price per square foot than non-qualified homes. These findings provide much-needed evidence that there is a market advantage for ENERGY STAR qualified homes that can achieve a positive rate of return on investments

Improving power theft detection using efficient clustering and ensemble classification

One of the main concerns of power generation systems around the world is power theft. This research proposes a framework that merges clustering and classification together in order to power theft detection. Due to the fact that most datasets do not have abnormal samples or are few, we have added abnormal samples to the original datasets using artificial attacks to create balance in the datasets and increase the correct detection rate. We improved the crow search algorithm (CSA) and used the weight feature of Crows to improve performance of clustering phase. Also, to create balance between diversification and intensification, we calculated the awareness probability parameter (AP) dynamically at iterations of the algorithm. To evaluate the performance, we used the cross validation technique have used the stacking technique in its training phase. The results of extensive experiments on three reference datasets showed high performance to detect power theft. The evaluation results showed that if the data is collected correctly and sufficiently, this framework can effectively detect power theft in any actual power grid. Also, for new attacks, if their patterns can be detected from the data, it is easily possible to implement these types of attacks

Human biomonitoring health surveillance for metals near a waste-to-energy incinerator: The 1-year post-operam study

This human biomonitoring (HBM) follow-up survey, within the SPoTT project, assessed the temporal and spatial trends of exposure to 18 metals in a cohort living around the waste-to-energy (WTE) incinerator of Turin (Italy) before (T0, 2013) and after 1-year of plant activity (T1, 2014). Urine of 380 adult individuals (186 exposed and 194 unexposed subjects, classified on fallout maps) were analyzed by sector field inductively coupled mass spectrometry. A decrease trend of the majority of metals in all subjects indicates that the overall air quality of the studied sites was not significantly compromised, also in proximity of the WTE plant, as corroborated also by air monitoring data of the regional agency. The only relevant exception was the higher Cr levels found at T1 than T0 in exposed subjects, suggesting a possible contribution from the WTE plant. Chromium, Mn and Pt urine levels were also higher in the site far from the WTE, in relation to other sources as vehicular traffic, industrial and civil activities. Whilst, As and Cd were influenced by fish intake and tobacco smoke. A very small number of individuals at T1, equally distributed in both areas, exceeded the health-based guidance values and so, at current knowledge, living near the Turin incineration did not significantly influence the exposure status of the population

Acoustic Filters for Sensors and Transducers: Energy Policy Instrument for Monitoring and Evaluating Holy Places and Their Habitants

The aim of the study is to present a brief overview of energy policy instrument for monitoring and evaluating holy places and their habitants with the aid of acoustic filters for sensors and transducers. A monitoring protocol for policy instrument is presented for noise protection and security from power systems. Methods of information and data collection are briefly elaborated. The power systems are classified as per source signals of solar power, electric power, light power, sound power, heat power, fluid power and fire power. The acoustic filters as per source of noise signals from power systems are defined. The filters are differentiated as per source signal of unwanted frequencies from solar power, electric power, light power, sound power, heat power, fluid power and fire power. Some examples of acoustic filters are mentioned as per source of noise signal. A slide rule for noise measurement is illustrated along with its noise grades and flag colors under limiting conditions. Some noise filtering results from various power systems of an outdoor duct are also tabulated. An overview of noise systems integration with command and control center is described. A brief discussion on management of holy places and their habitants through monitoring and evaluation is also mentioned

MEASURING CONSUMER PREFERENCES FOR ECOLABELED SEAFOOD: AN INTERNATIONAL COMPARISON

An analysis of consumer preferences for seafood labeled with information about environmental production attributes is introduced into the food labeling literature. International seafood ecolabeling programs have proposed to create market-based incentives for fisheries managers to promote sustainable fisheries. We investigate differences in consumer preferences for ecolabeled seafood across the United States and Norway. Using a contingent-choice telephone survey of random households in each nation, a wide range of factors is found to influence consumers' likelihood of purchasing ecolabeled seafood. Consumer preferences differ by price premium, species, consumer group, and certifying agency. The effect of these factors often differs between the United States and Norway, suggesting heterogeneity in international reactions to seafood ecolabels.Consumer/Household Economics,